Health Risk Reductions

We quantify the effect of federal UI on the trade-offs that individuals are willing to make with respect to county-level pandemic policies. We use choice experiments from an online survey, and both model, and correct for, systematic response/non-response propensities. When respondents are asked to assume that federal UI will be zero, they tend to be averse to losses in average household income but favorably disposed toward increased unemployment. With positive federal UI payments, however, respondents become more willing to accept losses in average household income but view increased unemployment less favorably.

We take advantage of a vintage 2003 general-population choice-experiment survey of U.S. residents designed to determine people’s willingness to bear the costs of public policies to reduce illnesses and avoid premature deaths in their communities. We re-estimate earlier models, omitting all respondent-specific individual characteristics and adding new county-level data on a variety of contextual variables circa 2003. Then we transfer our re-estimated model to the context of the 2020-21 COVID-19 pandemic, substituting 2020-era levels of the contextual variables, including county-level household incomes and unemployment rates. …

Studies of participant attention allocation in stated preference choice experiment (CE) studies have found mixed evidence that participants employ attribute non-attendance (ANA) as a decision heuristic or as a part of a fully rational search strategy. Many studies find that correcting for ANA has considerable effects on willingness-to-pay (WTP) estimates, but the right method of correction depends on the reasons for ANA. We conduct an experiment that, coupled with results from a previous survey, give us a uniquely suitable dataset to settle the heuristic-vs.-rationality debate.

We use monthly panel data on birth outcomes for more than 3000 U.S. counties, combined with the timing of heat waves during trimesters of gestation, to identify statistical relationships between prenatal exposure and adverse outcomes for the newborn or the mother.

We develop and estimate a utility-theoretic choice model to quantify demand for publicly provided medical treatment policies. We find diminishing marginal utility for increased recoveries and avoided premature deaths. We also show how willingness to pay for different types of treatment policies varies with the socio-demographic group that would benefit, with each respondent’s own gender, age, race, income, community ethnic fractionalization and immigrant composition, as well as the respondent’s expected private benefits from the policy, attitude toward government interventions and overall health care funding allocations.

For benefit-cost analysis of policies with respect to environmental and natural resources, economic researchers often require monetized values of households’ willingness to pay for reductions in risks to human life and health. I briefly recap some of the main issues in the related task of valuing reductions in the risk of death. These issues also account for our considerably smaller literature on valuing reductions in morbidity risks. An important distinction is the issue of valuation in the space of illnesses versus valuation in the space of illness attributes. I compare the requirements for environmental benefit-cost analysis with the limitations of the standard approaches taken in cost-effectiveness analysis in health economics, and I highlight some areas that are ripe for further research.

A choice model based on utility in a sequence of prospective future health states permits us to generalize the concept of the value of statistical life (VSL). Our representative national survey asks individuals to choose between costly risk-reducing programs and the status quo in randomized stated choice scenarios. Our model allows for separate marginal utilities for discounted net income and avoided illness years, post-illness years, and lost life-years. Our estimates permit calculation of overall willingness to pay to reduce risks for a wide variety of different prospective illness profiles. These can be benchmarked against the standard VSL as a special case.

We collect data about individual time preferences using a choice about payout options for hypothetical lottery winnings and model individual discount rates as a function of age, other socio-demographic variables and variables to capture health expectations. For older subjects, undesirable current health behaviors are better predicted by their back-casted discount rates at age 21. Assuming cohort effects are minimal, we infer that changing time preferences as people mature can lead to the development of health habits while they are young that are likely to be inconsistent with the preferences of their older future selves.

The time-tradeoff (TTO) method typically describes some period of years in an adverse health state and asks respondents how many (fewer) years in “full health” they would accept to avoid the longer time period in the adverse health state. TTO studies have produced many useful insights, such as the finding that tradeoffs willingly made depend upon the age and gender of the respondent. In contrast to surveys that focus specifically on time tradeoffs, we use a large general-population conjoint choice survey in the U.S. that was designed to permit estimation of willingness to pay (WTP) by different types of respondents to reduce their risks of suffering illnesses with specified time profiles of future symptoms and outcomes. These WTP functions were intended to serve as monetized benefits estimates for benefit-cost analysis of public policies to reduce both morbidity and mortality risks.

Our research identifies large systematic differences, by type of illness, in individual willingness to pay (WTP) to reduce the risk of the major health threats. These include five types of cancers (breast cancer, prostate cancer, colon cancer, lung cancer, and skin cancer), chronic heart disease (as well as sudden heart attacks), respiratory disease, strokes, diabetes, Alzheimer’s disease and traffic accidents. Our estimates take the form of individuals’ WTP to reduce the risk of experiencing specific illness profiles (i.e. the different patterns of sick-years, recovered/remission-years and/or lost life-years associated with each illness). Our results suggest that analyses which constrain the marginal utility parameters for different health states to be the same across all illnesses are too restrictive, causing the loss of valuable information for benefit-cost analyses of health, environmental and safety policies. We also find that the rank ordering of private willingness to pay for illness-specific risk reductions is highly correlated with public spending patterns by government agencies.

Using a large stated preference survey conducted across the U.S. and Canada, we assess differences in individual willingness to pay (WTP) for health risk reductions between the two countries. Our utility-theoretic choice model allows for systematically varying marginal utilities for avoided future time in different adverse health states (illness-years, recovered/remission years, and lost life-years). We find significant differences between Canadian and U.S. preferences. WTP also differs systematically with age, gender, education, and marital status, as well as a number of attitudinal and subjective health-perception variables. Age profiles for WTP are markedly different across the two countries. Canadians tend to display flatter age profiles, with peak WTP realized at older ages. (This paper featured as one chapter in Peter Stiffler’s Ph.D. dissertation at the University of Oregon.)

We show in a theoretical model that the benefit from additional attention to the marginal attribute within a choice set depends upon the expected utility loss from making a suboptimal choice if it is ignored. Guided by this analysis, we then develop an empirical method to measure an individual’s propensity to attend to attributes. As a proof of concept, we offer an empirical example of our method using a conjoint analysis of demand for programs to reduce health risks.

Background. Public policy can affect the allocation of resources between programs designed to prevent illnesses or injuries and programs designed to treat those who are already sick or injured. Information about preferences for treatment and prevention policies can help policy makers more effectively allocate public health resources among alternative uses. We estimate a random utility model of preferences for treatment and prevention policies and explore sources of systematic heterogeneity in preferences. We estimate marginal utility associated with avoided deaths to be about twice as high for prevention policies as for treatment policies and find statistically significant heterogeneity with respect to disease type, the group targeted by the policy, and respondent characteristics.

For economists, the term “value of a statistical life” (VSL) is an eminently reasonable label for the concept it describes. However, outside our discipline, this terminology has been singularly unhelpful. This article argues that there could be a considerable reduction in wasted resources if economists were to change this terminology to something less incendiary, and that this could help to increase the acceptance of benefit-cost analysis as an input to the decision-making process for environmental, health, and safety regulations. I propose that we change our standard unit of measurement and replace the VSL terminology with “willingness to swap (WTS) alternative goods and services for a microrisk reduction in the chance of sudden death.” Analogous terminology would be used for other types of risks to life and health. I also argue that economists’ continual pursuit of a single number for “the” VSL is misguided and can be misleading, especially if individual WTS is correlated with the magnitudes of the risk changes. Such “one-size-fits-all” VSLs also hinder our ability to understand the distributional consequences of risk-reducing policies or interventions. Estimates of aggregate risk reduction benefits need to reflect the particular type of risk reduction as well as the characteristics of the affected populations.

We examine patterns in adults’ willingness to pay for health-risk reductions. We allow both their marginal utilities of income and their marginal disutilities from health risks to vary systematically with the structures of their households. Demand by adults for programs which reduce their own health risks is found to be influenced by (1) their parenthood status, (2) the numbers of children in different age brackets currently in their households, (3) the ages of the adults themselves, (4) the latency period before they would fall ill, and (5) whether there will still be children in the household at that time. For younger adults, willingness to pay by parents is greater than for non-parents, and increases with each additional young child. For middle-aged adults, willingness to pay for corresponding risk reductions falls when teenagers are present and falls further with each additional teenager in the household.

We use this unique opportunity to explore the determinants of subjective choice difficulty to assess how well the customary reduced-form proxies are likely to capture this behavioral aspect of subjects’ interactions with stated-choice tasks. Common measures do not fully explain subjective choice difficulty, which also depends on the interplay among objective attribute-space complexity, the similarity of alternatives in utility space, and cognitive resource constraints.

Using a national survey and a discrete choice experiment format, we estimate demand for environmental polices to improve health. We use a richly detailed community-level approach that describes illnesses avoided, premature deaths avoided, policy duration, and the affected population size. We allow preferences for policy attributes to vary systematically with the scenario design, with the source of risk and type of health threat, and with respondent characteristics. Using a willingness to pay (WTP) framework similar to that used for studies of individual risk, we find that omission of illness information leads to an upward bias in estimates of the value of avoided premature deaths and that individuals view avoided deaths and avoided illnesses as substitutes. We also find evidence of strongly diminishing marginal utility in policy scope. Differences in marginal WTP from different sources of risk or types of illness appear very small relative to differences associated with respondent characteristics and/or perceptions. Self-interest strongly dominates altruistic considerations.

Individuals’ demands for programs targeting a particular illness are higher when there is a history of that illness and when subjective risks are higher. A history of other illnesses and greater other-illness subjective risks decrease demand. These comorbidity effects operate through the marginal utilities of both (i) adverse health states and (ii) income.

We develop and test an empirical model of individuals’ intertemporal demands for programs to mitigate health risks over the remaining years of their lives. We find qualified support for the Erhlich (2000) life-cycle model, which predicts that individuals expect to derive increasing marginal utility from reducing health risks that come to bear later in their lives. However, we also find that as individuals age, there appears to be a systematic downward shift in their anticipated schedule of marginal utility for risk reduction at future ages. Our model improves upon earlier work by differentiating between the respondent’s current age and the future ages at which they would experience adverse health states.